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Code and data used to generate the analyses in "Tempest: Temporal Dynamics in Anonymity Systems"
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path_inference
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pytricia @ ac4c3ac
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tempest
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CMakeLists.txt
LICENSE.md
README.md
requirements.txt
setup.py

README.md

Tempest

This repository contains some of the code and data used to generate the analyses found in

Tempest: Temporal Dynamics in Anonymity Systems
Ryan Wails, Yixin Sun, Aaron Johnson, Mung Chiang, Prateek Mittal
Proceedings on Privacy Enhancing Technologies (PoPETs), 2018
https://www.petsymposium.org/2018/paperlist.php

Please contact ryan dot wails @ nrl dot navy dot mil with questions.

Usage

Supported Platforms

Linux and Mac OSX are supported.

Prerequisites

To build this code, you will need to first install

Building

The recommended installation steps are

  1. Build the necessary executables and libraries
mkdir build
mkdir install
cd build
cmake -DCMAKE_INSTALL_PREFIX=../install ..
make && make install
  1. Setup and source a Python virtualenv
virtualenv -p python3 env
source env/bin/activate
  1. Install Python packages
git submodule init && git submodule update
cd pytricia && python3 setup.py build && python3 setup.py install && cd ..
pip install -r requirements.txt
python3 setup.py build && python3 setup.py install

Acknowledgements

This work was supported by the Office of Naval Research (ONR) and by the National Science Foundation (NSF) under grant numbers CNS-1527401, CNS-1423139 and CNS-1704105. The views expressed in this work are strictly those of the authors and do not necessarily reflect the official policy or position of ONR or NSF.

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